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Scaling Best Practices

Strategic approaches for efficient and cost-effective NodeGroup scaling.

Scaling Strategies​

Conservative Scaling​

Characteristics:

  • Scale 1-2 nodes at a time
  • Monitor impact after each operation
  • Lower risk of resource waste

Best For:

  • Production environments
  • Cost-sensitive workloads
  • Predictable traffic patterns

Aggressive Scaling​

Characteristics:

  • Scale rapidly to meet demand
  • Higher initial over-provisioning
  • Performance over cost efficiency

Best For:

  • High-availability requirements
  • Variable workloads
  • Revenue-critical systems

Predictive Scaling​

Characteristics:

  • Pattern-based scaling decisions
  • Scheduled operations
  • Data-driven approaches

Best For:

  • Scheduled workloads
  • Known traffic patterns
  • Business intelligence applications

Cost Optimization​

Scheduled Scaling​

Techniques:

  • Scale down during off-hours
  • Scale up before peak periods
  • Time-zone optimization
  • Maintenance window scaling

Benefits:

  • 40-60% reduction in off-peak costs
  • Automated cost management
  • Predictable resource usage

Reactive Scaling​

Approach:

  • Metric-based triggers
  • Threshold management
  • Cooldown periods
  • Cost monitoring

Thresholds:

  • Scale-up: CPU above 70%, Memory above 80%
  • Scale-down: CPU below 30%, Memory below 50% (sustained 15+ minutes)
  • Safety buffers: 20-30% resource buffer

Hybrid Scaling​

Model:

  • Baseline: 2-3 nodes minimum
  • Scheduled: +1-2 nodes during business hours
  • Reactive: +1-4 nodes based on demand
  • Maximum: Set reasonable limits to prevent runaway costs

Operational Excellence​

Capacity Planning​

Analysis:

  • Review 3-6 months of usage data
  • Factor in business growth plans
  • Account for seasonal variations
  • Maintain 20-30% capacity buffer

Monitoring Setup​

Essential Metrics:

  • Resource utilization (CPU, memory, disk, network)
  • Application performance (response times, error rates)
  • Scaling operations (success/failure rates, timing)
  • Cost tracking (real-time monitoring, budget variance)

Alert Configuration:

  • Resource utilization exceeding limits
  • Scaling operation notifications
  • Performance degradation alerts
  • Cost anomaly detection

Documentation​

Requirements:

  • Decision criteria for scaling operations
  • Impact assessment records
  • Lessons learned knowledge base
  • Configuration change tracking

Performance Optimization​

Application Considerations​

Workload Types:

  • Stateful vs stateless applications
  • Resource patterns and dependencies
  • Startup time considerations
  • Data locality requirements

Resource Distribution:

  • Configure Pod Disruption Budgets
  • Use node affinity rules
  • Proper resource requests/limits
  • Quality of Service class configuration

Network and Storage​

Network Planning:

  • Adequate IP address space
  • Load balancer configuration
  • Inter-node communication optimization
  • External connectivity verification

Storage Management:

  • Persistent volume scaling
  • Backup strategy adjustments
  • Performance monitoring
  • Data replication considerations